The 4-dimensional plant: enhanced mechanical canopy excitation for improved crop performance Grant uri icon

description

  • There is an urgent need to improve crop yield (tonnes per per hectare) in order to meet the needs of a growing global population and declining fertile agricultural land base. One of the current important targets for crop improvement is photosynthesis, a neglected trait in previous plant breeding efforts. Photosynthesis requires the uptake of carbon dioxide by leaves and its 'conversion' into carbohydrates using water and absorbed solar energy. However high rates of photosynthesis, on which yield depends, are sensitive to environmental changes such as light intensity, temperature and other factors. Crop productivity is the sum total of photosynthesis in leaves in a canopy, many of which shade each other and have different ages. We can calculate the potential productivity of whole canopies based on leaf photosynthetic attributes and other physical and physiological factors. When we do this the theoretical productivity tends to be much higher than the measured productivity which is partly due to the way leaves respond when re-constructed into a large three dimensional canopy. In this state, plants exist as a community which has emergent properties that we cannot necessarily predict from plants grown individually. If we can eliminate the gap between the theoretical and measured productivity we can achieve a step change in productivity. Photosynthetic rate is sensitive to light intensity. The difference in light intensities that exist within the canopy is significant and is affected by the architecture of the canopy i.e. the angle, shape and size of leaves and their position within 3 dimensional space. This means that the light intensity has great variability in space and time within canopies. Photosynthesis is not perfectly adapted to instantaneously match the fluctuations in light intensity - its lag results in substantial reductions in productivity and even water use efficiency. This proposal tackles a much ignored factor. Plants 'move' in light to moderate wind and this occurs on a daily basis, sometimes continually during growth which shifts the light patterns within the canopy. In recent work we found that movement has a strong effect on the rate at which light levels change in the canopy with strong implications for canopy photosynthesis. Such movement of the canopy plays a major part in how fast or slow light flecks are generated, and where in the canopy they appear. It seems that movement may enable the production of more rapid 'lightflecks', enhancing photosynthesis at the canopy level. We don't consider high speeds that result in damage, but we do incorporate lodging in our assessments of canopy viability. In a recent paper (Burgess et al (2016) Frontiers in Plant Science 7, 1392) showed that canopy movement has the means to alter photosynthetic responses at the canopy level. We also developed the techniques to generate high resolution 3D images of field grown wheat and rice canopies and for 'tracking' moving canopies. In this proposal we will bring these techniques together to produce models of canopies of rice and wheat and make these models move realistically in response to physical factors. At the same time we will use wheat and rice populations and panels with varied physical characteristics and responsiveness to wind and create data driven tracking movies of these canopies , making the 3D reconstruction move realistically. We will create methods for predicting light distribution in these canopies combining ray tracing techniques with field measurements of light distribution. We predict that the most productive property is for leaves to be highly responsive to wind at the top of the canopy but retaining a strong stiff stem. At the same time we will measure photosynthesis and biomass production in wheat lines which are amenable to genetic analysis so that we can discover the hereditary basis for the movement. Therefore the results will be used in plant breeding.

date/time interval

  • October 1, 2017 - December 31, 2020

total award amount

  • 655201 GBP

sponsor award ID

  • BB/R004633/1